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- Using active and passive acoustics to assess O2 production of a Posidonia oceanica meadowPublication . Felisberto, P.; Zabel, F.; Rodríguez, O. C.; Santos, P.; Jesus, S. M.; Champenois, W.; Borges, A. V.; Santos, RuiThis work discusses the data acquired during two experiments conducted in October 2011 and May 2013 in the Bay of la Revellata, Calvi, Corsica for the purpose of developing an acoustic system for monitoring the oxygen production of a seagrass meadow.
- Correlation between the acoustic noise field measured in a Posidonia oceanica bed and the photosynthetic activityPublication . Felisberto, P.; Zabel, F.; Rodríguez, O. C.; Santos, P.; Jesus, S. M.; Champenois, W.; Borges, A. V.; Santos, RuiDuring the period of one week, from May 8 to 15, 2013, acoustic data was gathered at three locations over a Posidonia oceanica bed in the Bay of Revellata, Corsica. Preliminary analysis of the acoustic data shows that the environmental noise field in the band 2-7kHz was dominant during the period. The noise in this band is generally associated with wind and surface agitation. However, the noise power was not significantly correlated with wind speed. On the contrary, the diel cycle of the noise power at three locations was highly correlated with the water column concentration of O2, as measured by optodes. These measurements of environmental noise have confirmed the correlation between active acoustic signals transmitted along a seagrass meadow and the photosynthetic activity of the plants observed in a previous experiment conducted in the same area .The results suggest that acoustic noise can be used as a proxy for the photosynthetic oxygen production of a Posidonia oceanica meadow. Therefore, this work is a contribution for the development of a low cost passive acoustic system to assess the primary production of coastal ecosystems .
- Comparing the resolution of Bartlett and MVDR estimators for bottom parameter estimation using pressure and vector sensor short array dataPublication . Felisberto, P.; Schneiderwind, J.; Santos, P.; Rodríguez, O. C.; Jesus, S. M.This work compares the resolution of a pressure and vector sensor based conventional Bartlett estimator, with their MVDR estimator counterparts, in the context of bottom characterization with a short vertical array. Santos et al. [1]demonstrated the gain of a vector sensor array (VSA) based linear estimator (Bartlett) for generic parameter estimation. Moreover, it was shown that for bottom characterization the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. The present work highlights the gain in parameter resolution of a VSA based MVDR estimator. It is shown, that also for a MVDR estimator, the vector sensor array data improves the resolution of parameter estimation. But, it is also shown, through simulations, that for bottom parameter estimation, the pressure based MVDR estimator has higher resolution and sidelobe attenuation than the VSA based Bartlett estimator. These results were verified for experimental data acquired by a four element, 30 cm long vertical VSA in the 8–14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA).
- On the usage of the particle velocity field for bottom characterizationPublication . Felisberto, P.; Rodríguez, O. C.; Santos, P.; Jesus, S. M.Vector sensors (VS) are devices that measure the vectorial particle velocity field. Compared with traditional hydrophone arrays that measure the acoustic pressure, systems based on VS present enhanced spatial filtering capabilities. The feasibility of bottom characterization with a 4-element 40cm length vector sensor array (VSA) in a frequency band of 8-14 kHz was recently demonstrated by Santos et al. The study suggests that systems based on VS outperform traditional hydrophone arrays, when considered in geoacoustic parameter estimation. Vector sensor data can improve the resolution of the estimators, moreover the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. Bearing in mind that actually VS are not widely available, the present work shows through simulations that using a narrow band signal and a vertical array which elements are pairs of hydrophones one can estimate the vertical particle field and attain a resolution for the bottom parameters similar to that obtained by a VSA. Based on a normal mode description of the pressure and particle velocity field, the resolution gain achieved by a linear estimator based on the vertical component only, is compared with similar estimators based on the pressure or on the horizontal component. Using simulations for different shallow water typical scenarios, we point out sensible values for the number of sensors, inter sensor spacing for system design as well as preferred equipment location for best results. This work is a contribution to the design of a compact array of hydrophones that takes advantage of the higher sensitivity of the vertical particle velocity field for geoacoustic parameter estimation.
- Estimating the multipath structure of an underwater channel using a single vector sensorPublication . Felisberto, P.; Rodríguez, O. C.; Jesus, S. M.This paper aims at estimating the multipath structure of an underwater acoustic channel using a single vector sensor. The multipath structure of an underwater acoustic channel measured by a single hydrophone from broadband signals is used for source localization or environmental monitoring applying model based methods. Usually these methods require a number of time consuming propagation model runs and an optimization procedure. A vector sensor measures the pressure and the particle velocity, thus in addition to delays and amplitudes estimated by a hydrophone can potentially estimate the direction (azimuth and elevation) of the different echoes in an impulse response. This additional information can be used to significantly reduce the number of propagation model runs and simplify the optimization procedure. Although, the estimate of the azimuth is relatively straightforward using a single vector sensor, the estimate of the elevation of the different echoes is difficult due to the signal bandwidth, low amplitude of the latter arrivals or sensitivity to phase errors of available devices, among others. This paper discusses the estimates of the direction of individual echoes observed in impulse responses gathered during the Makai’05 sea trial in the context of single vector sensor model based localization (azimuth, range and depth).
- Geoacoustic matched-field inversion using a vector sensor arrayPublication . Santos, P.; Felisberto, P.; Rodríguez, O. C.; Jesus, S. M.Vector sensors measure the acoustic pressure and the particle velocity components. This type of sensor has the ability to provide information in both vertical and azimuthal direction allowing increased directivity. These characteristics have been explored by many authors and most of the studies on vector sensors found in literature are related to direction of arrival (DOA) estimation. However, assembled into an array, a Vector Sensor Array (VSA) improves spatial filtering capabilities and can be used with advantage in other applications such as geoacoustic inversion. In this paper it will be shown that a reliable estimation of ocean bottom parameters, such as sediment compressional speed, density and compressional attenuation, can be obtained using high-frequency signals and a small aperture vertical VSA. The introduction of particle velocity on matched-field processing (MFP) techniques is going to be presented. It will be seen how MFP, usually done with acoustic pressure, can be adapted in order to incorporate the three components of the particle velocity. Comparisons between several processors based either in individual particle velocity components or using all the VSA outputs, are made for simulated and experimental data. The quaternion model, which is founded on hypercomplex algebra, thus more appropriate to represent the 4 dimensional VSA data, is also presented in the MFP context. A novel ray tracing model is used to generate field replicas that include both the acoustic pressure and the particle velocity outputs. The data considered herein was acquired by a four element vertical VSA in the 8-14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA). The results shows that, when the particle velocity is included it can significantly increase the resolution of bottom properties estimation and in some cases a similar result is obtained using only the vertical component of the particle velocity.
- Experimental results of underwater cooperative source localization using a single acoustic vector sensorPublication . Felisberto, Paulo; Rodríguez, O. C.; Santos, P. J.; Jesus, S. M.This paper aims at estimating the azimuth, range and depth of a cooperative broadband acoustic source with a single vector sensor in a multipath underwater environment, where the received signal is assumed to be a linear combination of echoes of the source emitted waveform. A vector sensor is a device that measures the scalar acoustic pressure field and the vectorial acoustic particle velocity field at a single location in space. The amplitudes of the echoes in the vector sensor components allow one to determine their azimuth and elevation. Assuming that the environmental conditions of the channel are known, source range and depth are obtained from the estimates of elevation and relative time delays of the different echoes using a ray-based backpropagation algorithm. The proposed method is tested using simulated data and is further applied to experimental data from the Makai’05 experiment, where 8–14 kHz chirp signals were acquired by a vector sensor array. It is shown that for short ranges, the position of the source is estimated in agreement with the geometry of the experiment. The method is low computational demanding, thus well-suited to be used in mobile and light platforms, where space and power requirements are limited.
- Seabed geoacoustic characterization with a vector sensor arrayPublication . Santos, P.; Rodríguez, O. C.; Felisberto, P.; Jesus, S. M.This paper proposes a vector sensor measurement model and the related Bartlett estimator based on particle velocity measurements for generic parameter estimation, illustrating the advantages of the Vector Sensor Array VSA . A reliable estimate of the seabed properties such as sediment compressional speed, density and compressional attenuation based on matched-field inversion MFI techniques can be achieved using a small aperture VSA. It is shown that VSAs improve the resolution of seabed parameter estimation when compared with pressure sensor arrays with the same number of sensors. The data considered herein was acquired by a four-element VSA in the 8–14 kHz band, during the Makai Experiment in 2005. The results obtained with the MFI technique are compared with those obtained with a method proposed by C. Harrison, which determines the bottom reflection loss as the ratio between the upward and downward beam responses. The results show a good agreement and are in line with the historical information for the area. The particle velocity information provided by the VSA increases significantly the resolution of seabed parameter estimation and in some cases reliable results are obtained using only the vertical component of the particle velocity.
- Comparing the resolution of Bartlett and MVDR processors for bottom parameter estimation using pressure and vector sensor short array dataPublication . Felisberto, P.; Schneiderwind, J.; Santos, P.; Rodríguez, O. C.; Jesus, S. M.This work compares the resolution of a pressure and vector sensor based conventional Bartlett estimator, with their MVDR estimator counterparts, in the context of bottom characterization with a short vertical array. Santos et al. [1] demonstrated the gain of a vector sensor array (VSA) based linear estimator (Bartlett) for generic parameter estimation. Moreover, it was shown that for bottom characterization the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. The present work highlights the gain in parameter resolution of a VSA based MVDR estimator. It is shown, that also for a MVDR estimator, the vector sensor array data improves the resolution of parameter estimation. But, it is also shown, through simulations, that for bottom parameter estimation, the pressure based MVDR estimator has higher resolution and sidelobe attenuation than the VSA based Bartlett estimator. These results were verified for experimental data acquired by a four element, 30 cm long vertical VSA in the 8–14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA).
- Variability of the ambient noise in a seagrass bedPublication . Felisberto, P.; Rodríguez, O. C.; Santos, P.; Zabel, F.; Jesus, S. M.This paper discusses the ambient noise acquired during the period of one week, from May 8 to 15, 2013 over a Posidonia oceanica bed in the Bay of la Revellata, Calvi, Corsica. The acoustic receivers were moored at 3 locations with water depth ranging from 2 to 20 m. Simultaneously with acoustic measurements, the dissolved O2 was measured by an array of optodes. The noise field in the band 2-7 kHz was dominant. The noise directionality and bottom reflectivity estimated using a short vertical array show a diurnal variability pattern. The mean noise power measured at all receivers shows also a diurnal variability pattern, which is negatively correlated with the O2 dissolved in the water. Changes in noise power between the night (highest noise power) and day period (lowest noise power) as high as 5 dB were observed at the various locations. These results suggest that the ambient noise power and directionality are correlated with the photosynthetic activity of the seagrass meadow and that a passive acoustic system can be used to monitor the O2 production of the meadow. © 2014 IEEE.